CS Special Seminar: Yanqi Su "Shaping the Future of Exploratory Testing with Knowledge Graphs and LLMs: Comprehensive, Adaptive, and Intelligent"
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Shaping the Future of Exploratory Testing with Knowledge Graphs and LLMs: Comprehensive, Adaptive, and Intelligent
Yanqi Su
Technical University of Munich
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Abstract: Software failures, whether crashes, usability issues, or policy violations, can lead to frustration, exclusion, and even financial or legal consequences. This talk focuses on ensuring software quality by making it reliable, inclusive, and trustworthy, so it works as expected for everyone. To that end, it introduces an intelligent testing system that combines large language models with structured testing knowledge to plan, execute, and interpret tests with human-like reasoning. This approach enables scalable, intelligent evaluation of software behavior, moving beyond manual testing toward fully automated, human-centered quality assurance.
Bio: Yanqi Su is a postdoctoral fellow at the Technical University of Munich (TUM), working in the Software Engineering & AI chair. Her research interests include software testing, knowledge graphs in software engineering, software repository mining, multi-modal models, and human-computer interaction.
Department of Computer Science
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